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The next web

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    Time flies.
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    It's actually almost 20 years ago
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    when I wanted to reframe the way we use information,
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    the way we work together: I invented the World Wide Web.
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    Now, 20 years on, at TED,
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    I want to ask your help in a new reframing.
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    So going back to 1989,
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    I wrote a memo suggesting the global hypertext system.
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    Nobody really did anything with it, pretty much.
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    But 18 months later -- this is how innovation happens --
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    18 months later, my boss said I could do it on the side,
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    as a sort of a play project,
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    kick the tires of a new computer we'd got.
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    And so he gave me the time to code it up.
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    So I basically roughed out what HTML should look like:
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    hypertext protocol, HTTP;
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    the idea of URLs, these names for things
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    which started with HTTP.
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    I wrote the code and put it out there.
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    Why did I do it?
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    Well, it was basically frustration.
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    I was frustrated -- I was working as a software engineer
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    in this huge, very exciting lab,
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    lots of people coming from all over the world.
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    They brought all sorts of different computers with them.
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    They had all sorts of different data formats,
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    all sorts, all kinds of documentation systems.
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    So that, in all that diversity,
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    if I wanted to figure out how to build something
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    out of a bit of this and a bit of this,
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    everything I looked into, I had to connect to some new machine,
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    I had to learn to run some new program,
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    I would find the information I wanted in some new data format.
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    And these were all incompatible.
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    It was just very frustrating.
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    The frustration was all this unlocked potential.
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    In fact, on all these discs there were documents.
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    So if you just imagined them all
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    being part of some big, virtual documentation system in the sky,
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    say on the Internet,
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    then life would be so much easier.
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    Well, once you've had an idea like that it kind of gets under your skin
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    and even if people don't read your memo --
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    actually he did, it was found after he died, his copy.
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    He had written, "Vague, but exciting," in pencil, in the corner.
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    (Laughter)
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    But in general it was difficult -- it was really difficult to explain
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    what the web was like.
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    It's difficult to explain to people now that it was difficult then.
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    But then -- OK, when TED started, there was no web
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    so things like "click" didn't have the same meaning.
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    I can show somebody a piece of hypertext,
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    a page which has got links,
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    and we click on the link and bing -- there'll be another hypertext page.
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    Not impressive.
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    You know, we've seen that -- we've got things on hypertext on CD-ROMs.
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    What was difficult was to get them to imagine:
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    so, imagine that that link could have gone
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    to virtually any document you could imagine.
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    Alright, that is the leap that was very difficult for people to make.
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    Well, some people did.
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    So yeah, it was difficult to explain, but there was a grassroots movement.
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    And that is what has made it most fun.
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    That has been the most exciting thing,
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    not the technology, not the things people have done with it,
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    but actually the community, the spirit of all these people
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    getting together, sending the emails.
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    That's what it was like then.
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    Do you know what? It's funny, but right now it's kind of like that again.
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    I asked everybody, more or less, to put their documents --
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    I said, "Could you put your documents on this web thing?"
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    And you did.
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    Thanks.
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    It's been a blast, hasn't it?
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    I mean, it has been quite interesting
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    because we've found out that the things that happen with the web
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    really sort of blow us away.
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    They're much more than we'd originally imagined
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    when we put together the little, initial website
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    that we started off with.
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    Now, I want you to put your data on the web.
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    Turns out that there is still huge unlocked potential.
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    There is still a huge frustration
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    that people have because we haven't got data on the web as data.
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    What do you mean, "data"? What's the difference -- documents, data?
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    Well, documents you read, OK?
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    More or less, you read them, you can follow links from them, and that's it.
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    Data -- you can do all kinds of stuff with a computer.
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    Who was here or has otherwise seen Hans Rosling's talk?
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    One of the great -- yes a lot of people have seen it --
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    one of the great TED Talks.
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    Hans put up this presentation
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    in which he showed, for various different countries, in various different colors --
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    he showed income levels on one axis
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    and he showed infant mortality, and he shot this thing animated through time.
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    So, he'd taken this data and made a presentation
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    which just shattered a lot of myths that people had
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    about the economics in the developing world.
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    He put up a slide a little bit like this.
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    It had underground all the data
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    OK, data is brown and boxy and boring,
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    and that's how we think of it, isn't it?
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    Because data you can't naturally use by itself
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    But in fact, data drives a huge amount of what happens in our lives
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    and it happens because somebody takes that data and does something with it.
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    In this case, Hans had put the data together
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    he had found from all kinds of United Nations websites and things.
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    He had put it together,
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    combined it into something more interesting than the original pieces
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    and then he'd put it into this software,
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    which I think his son developed, originally,
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    and produces this wonderful presentation.
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    And Hans made a point
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    of saying, "Look, it's really important to have a lot of data."
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    And I was happy to see that at the party last night
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    that he was still saying, very forcibly, "It's really important to have a lot of data."
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    So I want us now to think about
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    not just two pieces of data being connected, or six like he did,
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    but I want to think about a world where everybody has put data on the web
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    and so virtually everything you can imagine is on the web
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    and then calling that linked data.
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    The technology is linked data, and it's extremely simple.
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    If you want to put something on the web there are three rules:
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    first thing is that those HTTP names --
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    those things that start with "http:" --
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    we're using them not just for documents now,
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    we're using them for things that the documents are about.
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    We're using them for people, we're using them for places,
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    we're using them for your products, we're using them for events.
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    All kinds of conceptual things, they have names now that start with HTTP.
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    Second rule, if I take one of these HTTP names and I look it up
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    and I do the web thing with it and I fetch the data
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    using the HTTP protocol from the web,
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    I will get back some data in a standard format
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    which is kind of useful data that somebody might like to know
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    about that thing, about that event.
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    Who's at the event? Whatever it is about that person,
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    where they were born, things like that.
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    So the second rule is I get important information back.
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    Third rule is that when I get back that information
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    it's not just got somebody's height and weight and when they were born,
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    it's got relationships.
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    Data is relationships.
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    Interestingly, data is relationships.
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    This person was born in Berlin; Berlin is in Germany.
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    And when it has relationships, whenever it expresses a relationship
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    then the other thing that it's related to
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    is given one of those names that starts HTTP.
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    So, I can go ahead and look that thing up.
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    So I look up a person -- I can look up then the city where they were born; then
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    I can look up the region it's in, and the town it's in,
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    and the population of it, and so on.
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    So I can browse this stuff.
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    So that's it, really.
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    That is linked data.
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    I wrote an article entitled "Linked Data" a couple of years ago
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    and soon after that, things started to happen.
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    The idea of linked data is that we get lots and lots and lots
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    of these boxes that Hans had,
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    and we get lots and lots and lots of things sprouting.
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    It's not just a whole lot of other plants.
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    It's not just a root supplying a plant,
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    but for each of those plants, whatever it is --
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    a presentation, an analysis, somebody's looking for patterns in the data --
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    they get to look at all the data
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    and they get it connected together,
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    and the really important thing about data
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    is the more things you have to connect together, the more powerful it is.
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    So, linked data.
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    The meme went out there.
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    And, pretty soon Chris Bizer at the Freie Universitat in Berlin
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    who was one of the first people to put interesting things up,
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    he noticed that Wikipedia --
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    you know Wikipedia, the online encyclopedia
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    with lots and lots of interesting documents in it.
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    Well, in those documents, there are little squares, little boxes.
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    And in most information boxes, there's data.
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    So he wrote a program to take the data, extract it from Wikipedia,
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    and put it into a blob of linked data
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    on the web, which he called dbpedia.
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    Dbpedia is represented by the blue blob in the middle of this slide
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    and if you actually go and look up Berlin,
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    you'll find that there are other blobs of data
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    which also have stuff about Berlin, and they're linked together.
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    So if you pull the data from dbpedia about Berlin,
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    you'll end up pulling up these other things as well.
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    And the exciting thing is it's starting to grow.
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    This is just the grassroots stuff again, OK?
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    Let's think about data for a bit.
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    Data comes in fact in lots and lots of different forms.
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    Think of the diversity of the web. It's a really important thing
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    that the web allows you to put all kinds of data up there.
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    So it is with data. I could talk about all kinds of data.
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    We could talk about government data, enterprise data is really important,
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    there's scientific data, there's personal data,
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    there's weather data, there's data about events,
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    there's data about talks, and there's news and there's all kinds of stuff.
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    I'm just going to mention a few of them
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    so that you get the idea of the diversity of it,
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    so that you also see how much unlocked potential.
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    Let's start with government data.
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    Barack Obama said in a speech,
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    that he -- American government data would be available on the Internet
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    in accessible formats.
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    And I hope that they will put it up as linked data.
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    That's important. Why is it important?
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    Not just for transparency, yeah transparency in government is important,
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    but that data -- this is the data from all the government departments
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    Think about how much of that data is about how life is lived in America.
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    It's actual useful. It's got value.
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    I can use it in my company.
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    I could use it as a kid to do my homework.
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    So we're talking about making the place, making the world run better
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    by making this data available.
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    In fact if you're responsible -- if you know about some data
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    in a government department, often you find that
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    these people, they're very tempted to keep it --
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    Hans calls it database hugging.
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    You hug your database, you don't want to let it go
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    until you've made a beautiful website for it.
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    Well, I'd like to suggest that rather --
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    yes, make a beautiful website,
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    who am I to say don't make a beautiful website?
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    Make a beautiful website, but first
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    give us the unadulterated data,
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    we want the data.
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    We want unadulterated data.
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    OK, we have to ask for raw data now.
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    And I'm going to ask you to practice that, OK?
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    Can you say "raw"?
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    Audience: Raw.
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    Tim Berners-Lee: Can you say "data"?
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    Audience: Data.
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    TBL: Can you say "now"?
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    Audience: Now!
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    TBL: Alright, "raw data now"!
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    Audience: Raw data now!
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    Practice that. It's important because you have no idea the number of excuses
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    people come up with to hang onto their data
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    and not give it to you, even though you've paid for it as a taxpayer.
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    And it's not just America. It's all over the world.
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    And it's not just governments, of course -- it's enterprises as well.
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    So I'm just going to mention a few other thoughts on data.
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    Here we are at TED, and all the time we are very conscious
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    of the huge challenges that human society has right now --
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    curing cancer, understanding the brain for Alzheimer's,
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    understanding the economy to make it a little bit more stable,
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    understanding how the world works.
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    The people who are going to solve those -- the scientists --
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    they have half-formed ideas in their head,
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    they try to communicate those over the web.
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    But a lot of the state of knowledge of the human race at the moment
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    is on databases, often sitting in their computers,
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    and actually, currently not shared.
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    In fact, I'll just go into one area --
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    if you're looking at Alzheimer's, for example,
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    drug discovery -- there is a whole lot of linked data which is just coming out
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    because scientists in that field realize
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    this is a great way of getting out of those silos,
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    because they had their genomics data in one database
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    in one building, and they had their protein data in another.
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    Now, they are sticking it onto -- linked data --
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    and now they can ask the sort of question, that you probably wouldn't ask,
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    I wouldn't ask -- they would.
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    What proteins are involved in signal transduction
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    and also related to pyramidal neurons?
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    Well, you take that mouthful and you put it into Google.
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    Of course, there's no page on the web which has answered that question
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    because nobody has asked that question before.
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    You get 223,000 hits --
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    no results you can use.
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    You ask the linked data -- which they've now put together --
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    32 hits, each of which is a protein which has those properties
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    and you can look at.
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    The power of being able to ask those questions, as a scientist --
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    questions which actually bridge across different disciplines --
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    is really a complete sea change.
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    It's very very important.
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    Scientists are totally stymied at the moment --
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    the power of the data that other scientists have collected is locked up
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    and we need to get it unlocked so we can tackle those huge problems.
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    Now if I go on like this, you'll think that all the data comes from huge institutions
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    and has nothing to do with you.
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    But, that's not true.
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    In fact, data is about our lives.
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    You just -- you log on to your social networking site,
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    your favorite one, you say, "This is my friend."
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    Bing! Relationship. Data.
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    You say, "This photograph, it's about -- it depicts this person. "
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    Bing! That's data. Data, data, data.
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    Every time you do things on the social networking site,
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    the social networking site is taking data and using it -- re-purposing it --
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    and using it to make other people's lives more interesting on the site.
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    But, when you go to another linked data site --
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    and let's say this is one about travel,
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    and you say, "I want to send this photo to all the people in that group,"
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    you can't get over the walls.
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    The Economist wrote an article about it, and lots of people have blogged about it --
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    tremendous frustration.
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    The way to break down the silos is to get inter-operability
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    between social networking sites.
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    We need to do that with linked data.
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    One last type of data I'll talk about, maybe it's the most exciting.
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    Before I came down here, I looked it up on OpenStreetMap
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    The OpenStreetMap's a map, but it's also a Wiki.
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    Zoom in and that square thing is a theater -- which we're in right now --
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    The Terrace Theater. It didn't have a name on it.
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    So I could go into edit mode, I could select the theater,
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    I could add down at the bottom the name, and I could save it back.
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    And now if you go back to the OpenStreetMap. org,
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    and you find this place, you will find that The Terrace Theater has got a name.
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    I did that. Me!
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    I did that to the map. I just did that!
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    I put that up on there. Hey, you know what?
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    If I -- that street map is all about everybody doing their bit
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    and it creates an incredible resource
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    because everybody else does theirs.
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    And that is what linked data is all about.
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    It's about people doing their bit
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    to produce a little bit, and it all connecting.
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    That's how linked data works.
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    You do your bit. Everybody else does theirs.
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    You may not have lots of data which you have yourself to put on there
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    but you know to demand it.
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    And we've practiced that.
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    So, linked data -- it's huge.
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    I've only told you a very small number of things
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    There are data in every aspect of our lives,
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    every aspect of work and pleasure,
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    and it's not just about the number of places where data comes,
  • 15:13 - 15:16
    it's about connecting it together.
  • 15:16 - 15:19
    And when you connect data together, you get power
  • 15:19 - 15:22
    in a way that doesn't happen just with the web, with documents.
  • 15:22 - 15:26
    You get this really huge power out of it.
  • 15:26 - 15:29
    So, we're at the stage now
  • 15:29 - 15:33
    where we have to do this -- the people who think it's a great idea.
  • 15:33 - 15:36
    And all the people -- and I think there's a lot of people at TED who do things because --
  • 15:36 - 15:38
    even though there's not an immediate return on the investment
  • 15:38 - 15:41
    because it will only really pay off when everybody else has done it --
  • 15:41 - 15:45
    they'll do it because they're the sort of person who just does things
  • 15:45 - 15:48
    which would be good if everybody else did them.
  • 15:48 - 15:50
    OK, so it's called linked data.
  • 15:50 - 15:52
    I want you to make it.
  • 15:52 - 15:54
    I want you to demand it.
  • 15:54 - 15:56
    And I think it's an idea worth spreading.
  • 15:56 - 15:57
    Thanks.
  • 15:57 - 16:00
    (Applause)
Title:
The next web
Speaker:
Tim Berners-Lee
Description:

20 years ago, Tim Berners-Lee invented the World Wide Web. For his next project, he's building a web for open, linked data that could do for numbers what the Web did for words, pictures, video: unlock our data and reframe the way we use it together.

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Video Language:
English
Team:
closed TED
Project:
TEDTalks
Duration:
16:32
Thu-Huong Ha edited English subtitles for The next web
Thu-Huong Ha edited English subtitles for The next web
Thu-Huong Ha edited English subtitles for The next web
TED added a translation

English subtitles

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